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SUMMARY:Genomic and Metabolic analysis of a pathogen causing dental diseas
 e  - Zihan Tian
DTSTART:20250618T160000Z
DTEND:20250618T163000Z
UID:TALK233476@talks.cam.ac.uk
CONTACT:Pietro Lio
DESCRIPTION:Various studies indicate that microbial dysbiosis is associate
 d with oral and systemic diseases (Han\, 2015). Fusobacterium nucleatum (F
 .nucleatum)\, a Gram-negative anaerobe naturally found in the oral cavity 
 of humans\, contributes to periodontal disease\, as well as oral and color
 ectal cancers (Patel et al.\, 2022\; Queen et al.\, 2025). The association
  of F. nucleatum with oral squamous cell carcinoma (OSCC) highlights its r
 ole via oncogenic signaling pathways and has metabolic adaptability in the
  tumor microenvironments (Lim et al.\, 2025).To better understand F. nucle
 atum metabolic capabilities and environmental factors that promote cancer-
 associated strain growth in a specific niche\, such as the oral cavity\, t
 his study constructs a comprehensive metabolic model to predict its growth
  dynamics by leveraging machine learning-informed genome-scale metabolic m
 odeling (GEM) (Kapatral et al.\, 2002). This study wished to facilitate or
 al cancer screening and early diagnosis\, thus focusing on Fusobacterium n
 ucleatum strain ATCC 25586\, which naturally appears in the oral cavity. \
 n\nTo systematically investigate F. nucleatum’s metabolic behavior\, COB
 RApy\, a Python-based constraint-based modeling framework\, is used for it
  allows mechanistic interpretation\, genome-scale predictions of microbial
  growth under defined environmental constraints. COBRA-based features (e.g
 .\, nutrient flux profiles\, biomass predictions) can be used later as inp
 uts to train machine learning models that predict disease associations or 
 therapeutic responses based on a specific oral nutrient environment (Heire
 ndt et al.\, 2019).\n\nTo generate a metabolic model that COBRApy can anal
 yze\, the complete genome of F. nucleatum ATCC 25586 was initially annotat
 ed using Prokka\, providing a detailed catalog of its genetic components. 
 The annotated genome was then utilized with CarveMe to reconstruct a genom
 e-scale metabolic model\, comprising 1914 reactions and 1339 metabolites\,
  with 582 associated genes. Flux Balance Analysis (FBA) was applied to det
 ermine the optimal growth rate\, which was predicted to be 67.42h⁻¹ und
 er ideal nutrient-rich conditions. The flux through the biomass reaction r
 epresents the rate at which the bacterium produces those metabolites neces
 sary for its growth (e.g.\, amino acids\, lipids\, cofactors\, and protein
 s). The biomass flux returned by COBRA is the specific growth rate that ca
 n be used to calculate the specific biomass of the bacteria at a specific 
 time using an exponential function. Therefore\, biomass flux can be used a
 s an indicator of the growth rate of the bacterium. 
LOCATION:Online
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